The purpose of this tutorial is to give you some experience putting some data on a map. Mapping data is a way of visualising your data in geographical space. The science dealing with spatial information is referred to as Geographical Information Science or GIS for short. GIS is a relatively new field — it started in the 1970’s. It used to be that computerised GIS was only available to companies and universities that had expensive computer equipment. These days, anyone with a personal computer or laptop can use GIS software. Over time GIS Applications have also become easier to use –– it used to require a lot of training to use a GIS Application, but now it is much easier to get started in GIS even for amateurs and casual users. As we described above, GIS is more than just software, it refers to all aspects of managing and using digital geographical data. In the tutorial that follows we will be focusing on GIS Software. This tutorial is intended as a crash course in dealing with spatial data.

However you should be aware that there is a whole field behind this, and that you be motivated to learn more about this area, in order to make sure that any application you create has gounding in this field. Make sure that you are drawing meaningful conclusions from your data, and that you are confident in understanding the meaning behind what you are presenting in your maps.

I strongly recommend that you consult some resources, such as these books:

A topic that this tutorial does not cover is that of spatial relationships. The First Law of Geography, according to Waldo Tobler, is that “everything is related to everything else, but near things are more related than distant things.” This first law is the foundation of the fundamental concepts of spatial dependence and spatial autocorrelation. These concepts tend to account for spatial dependence in data, by using things like spatial weighting. We simply do not have time to cover these here, but it might be worth reading a bit around these concepts if you will be dealing with spatial data at all during your internship.

A quick introduction of terms

Geospatial Perspective - The Basics

Geospatial analysis provides a distinct perspective on the world, a unique lens through which to examine events, patterns, and processes that operate on or near the surface of our planet. Ultimately geospatial analysis concerns what happens where, and makes use of geographic information that links features and phenomena on the Earth’s surface to their locations.

We can talk about a few different concepts when it comes to spatial information. These are:

  • Place
  • Attributes
  • Objects

Place

At the center of all spatial analysis is the concept of place. People identify with places of various sizes and shapes, from the room with the parcel of land, to the neighbourhood, to the city, the country, the state or the nation state. Plcaes often have names, and people use these to talk about and distinguesh names. Names can be official. Places also change continually as people move. The basis of rigorous and precise definition of place is a coordinate system, a set of measurements that allows place to be specified unambiguously and in a way that is meaningful to everyone.

Attributes

Attribute has become the preferred term for any recorded characteristoc or property of a place. A place’s name is an obvious example of an attribute. But there can be other pices of information, such as numer of crimes in a neighbourhood, or the GDP of a country. Within GIS the term ‘attributes’ usually refers to records in a data table associated with individual features in a vector map or cells in a grid (raster or image file). These data behave exactly as data you have encountered in your data analysis courses. The rows represent observations, and the columns represent variables. The variables can be numeric or categorical, and depending on what they are, you can apply different methods to making sense of them.

Objects

In spatial analysis it is customary to refer to places as objects. These objects can be a whole country, or a road. In studies of climate change, the objects of interest might be weather stations of minimal extent, and will be represented as points. On the other hand amy studies of social or economic patterns may need to consider the two-dimenstional extent of places, which will therefore be represented as areas. These representations of the world are part of what is called the vector data model: A representation of the world using points, lines, and polygons. Vector models are useful for storing data that has discrete boundaries, such as country borders, land parcels, and streets. This is made up of points, lines, and areas (polygons):

  • Points
    • Points are pairs of coordinates, in latitude/lngitude or some other standard system
  • Lines
    • Lines are ordered sequences of points connected by straight lines
  • Areas (polygons)
    • Areas are ordered rigns of points, also connected by straight lines to form polygons. It can contain holes, or be linked with separate islands.

Objects can also be Raster data. Raster data is made up of pixels (or cells), and each pixel has an associated value. Simplifying slightly, a digital photograph is an example of a raster dataset where each pixel value corresponds to a particular colour. In GIS, the pixel values may represent elevation above sea level, or chemical concentrations, or rainfall etc. The key point is that all of this data is represented as a grid of (usually square) cells. You will most likely be dealing with vector data in your internships, so we will be focusing on these.

Maps

Historically maps have been the primary means to store and communicate spatial data. Objects and their attributes can be readily depicted, and the human eye can quickly discern patterns and anomalies in a well-designed map.

Map projections

Map projections try to portray the surface of the earth or a portion of the earth on a flat piece of paper or computer screen. A coordinate reference system (CRS) then defines, with the help of coordinates, how the two-dimensional, projected map in your GIS is related to real places on the earth. The decision as to which map projection and coordinate reference system to use, depends on the regional extent of the area you want to work in, on the analysis you want to do and often on the availability of data.

A traditional method of representing the earth’s shape is the use of globes. When viewed at close range the earth appears to be relatively flat. However when viewed from space, we can see that the earth is relatively spherical. Maps, are representations of reality. They are designed to not only represent features, but also their shape and spatial arrangement. Each map projection has advantages and disadvantages. The best projection for a map depends on the scale of the map, and on the purposes for which it will be used. For your purposes, you just need to understand that essentially there are different ways to flatten out the earth, in order to get it into a 2-dimensional map.

The process of creating map projections can be visualised by positioning a light source inside a transparent globe on which opaque earth features are placed. Then project the feature outlines onto a two-dimensional flat piece of paper. Different ways of projecting can be produced by surrounding the globe in a cylindrical fashion, as a cone, or even as a flat surface. Each of these methods produces what is called a map projection family. Therefore, there is a family of planar projections, a family of cylindrical projections, and another called conical projections see figure_projection_families

figure_projection_families

figure_projection_families

With the help of coordinate reference systems (CRS) every place on the earth can be specified by a set of three numbers, called coordinates. In general CRS can be divided into projected coordinate reference systems (also called Cartesian or rectangular coordinate reference systems) and geographic coordinate reference systems.

The use of Geographic Coordinate Reference Systems is very common. They use degrees of latitude and longitude and sometimes also a height value to describe a location on the earth’s surface. The most popular is called WGS 84. This is the one you will most likely be using, and if you get your data in latitude and longitude, then this is the CRS you are working in. It is also possible that you will be using a projected CRS. This two-dimensional coordinate reference system is commonly defined by two axes. At right angles to each other, they form a so called XY-plane. The horizontal axis is normally labelled X, and the vertical axis is normally labelled Y. Working with data in the UK, you are most likely to be using what is often called British National Grid (BNG). The Ordnance Survey National Grid reference system is a system of geographic grid references used in Great Britain, different from using Latitude and Longitude. In this case, points will be defined by “Easting” and “Northing” rather than “Longitude” and “Latitude”. It basically divides the UK into a series of squares, and uses references to these to locate something. The most common usage is the six figure grid reference, employing three digits in each coordinate to determine a 100 m square. For example, the grid reference of the 100 m square containing the summit of Ben Nevis is NN 166 712. Grid references may also be quoted as a pair of numbers: eastings then northings in metres, measured from the southwest corner of the SV square. For example, the grid reference for Sullom Voe oil terminal in the Shetland Islands may be given as HU396753 or 439668,1175316

BNG

BNG

This will be important later on when we are linking data from different projections, or when you look at your map and you try to figure out why it might look “squished”.

Networks

We already mentioned lines that constitute objects of spatial data, such as streets, roads, railroads, etc. Networks constitute one-dimensional structures embedded in two or three dimensions. Discrete point objects may be distributed on the netowkr, representing phenomena such as landmarks, or observation points. Mathematically, a network forms a graph, and many techniques developed for graphs have application to networks. These include various ways of measuring a network’s connectivity, or of finding the shortest path between pairs of points on a network. You can have a look at the lesson on network analysis in the QGIS documentation

Density estimation

One of the more useful concepts in spacial analysis is density - the density of humans in a crowded city, or the density of retail stores in a shopping centre. Mathematically, the density of some kind of object is calculated by counting the number of such objects in an area, and dividing by the size of the area. To read more about this, I recommend Silverman, Bernard W. Density estimation for statistics and data analysis. Vol. 26. CRC press, 1986.

Summary

Right so hopefully this gives you a few things to think about. Be sure that you are confident to know about:

  • Spatial objects - what they are and how they are represented
  • Attributes - the bits of information that belong to your spatial objects
  • Maps and projections - especially what WSG84 and BNG mean, and why it’s important that you know what CRS your data have

And if you’re interested you can read up about density and networks. Again we are not really covering those here, but they are something that you might come accross in your internship, depending on what sort of data you will be working with.

The software

Before we start, let’s familiarise ourselves with the software we will be using. Now it’s possible that you will enter a workplace where they will be using different systems. Many government agencies might be using something called MapInfo. Agencies with a bit more money are likely to be using ESRI Arc GIS. If you are forced to use these (and if there are people using this and there is support where you are, then you might as well) then don’t worry, the concepts are more or less the same. You will be able to search the help function for the same terms, or look through any documentation available and search through that on how to exactly carry out what it is that you want to do. However the issue with these GIS is that they are proprietary, and they cost a lot of money to use. They also have paid-for training and support, which you cannot openly access. QGIS on the other hand is entirely free, and because it’s open source, there is documentation and support available everywhere. If you are not sure how to do something in QGIS, all you have to do is GOOGLE IT, and there will be many useful answers for you to browse through and fix your issue. Similarly if you get an error message, just google it, and you will find help.

If you are using your own laptop, or the organisation gives you the option of choosing what you want to use, you can easily make a case for QGIS as it is totally free and therefore gives no cost to the organisation, or to you if you want to use it on your own laptop. Also because it is open source, anyone can contribute, and so you can have these plugins, which people write to help them sovle very specific problems. But more about this in the next section, where I tell you all about QGIS.

QGIS

The main tool we will be using is QGIS. QGIS functions as geographic information system (GIS) software, allowing users to analyze and edit spatial information, in addition to composing and exporting graphical maps. Throughout this tutorial I assume that you have some experience using QGIS (or a similar GIS) and you are familiar with spatial data handling and analysis. If you are interested, you can learn more about QGIS here:

Plugins

QGIS has a variety of plugins that you can download, and use for your work. Plugins in QGIS add useful features to the software. Plugins are written by QGIS developers and other independent users who want to extend the core functionality of the software. These plugins are made available in QGIS for all the users.

You can see a tutorial for installing and using plugins here

While we don’t use plugins in tutorials, sometimes when you might be googling how to do something in QGIS the answer might be to use the “such and such plugin”. In that case you will have to install the plugin first, to use it!

Getting Practical

Right, let’s make some maps!

In this tutorial we will import a spapefile, we will consider its projection, and also join some tabular data, to be able to look at such data on a map. Then we will then import some x & y coordinates, we will consider the projection of that as well, and do some reprojection, to align our two spatial objects. We will then use a function called points in polygon to count the number of points in each polygon in the shapefile, and use this to create a thematic map. Hopefully while carrying out these tasks you will learn to:

So let’s get started.

First things first, you have to create a folder where you will work. It’s important to be organised and consistent. All your files should be saved in this one folder, both those you import and those you export from QGIS. So create a folder for your work first.

Then, let’s open up the QGIS software.

Take a moment to have a look at this, you can see there are quite a lot of buttons there on the side and the top. It might be worth going through this short video that outlines the interfact for you quickly (and gives some more tips about why QGIS is a great choice for GIS)

We will return to this shortly. But let’s step away for a moment, and talk about how to get some data.

Find a shapefile

You will often need a boundary shapefile for your data analysis. Sometimes you will be given spatial data to begin with, such as a shapefile, or point coordinates with latitudes and longitudes (or eastings and northings). But other times you might have to find this yourself, and join the non-spatial data to these. This latter case is what the first part of this tutorial will demonstrate. In this case, you will have to source the spatial data yourself.

You can acquire spatial data from various sources. An example is Census Boundary Data. You can read more about that here. “Boundary data are a digitised representation of the underlying geography of the census”. Census Geography is often used in research and spatial analysis because it is divided into units based on population counts, created to creat comparable units, rather than administrative boundaries such as wards or police force areas. However depending on your research question and the context for your analysis, you might be using different units. The hierarchy of the census geographies goes from Country to Local Authority to Middle Layer Super Output Area (MSOA) to Lower Layer Super Output Area (LSOA) to Output Area:

Here we will get some boundaries for Manchester. Let’s use the LSOA level. These are geographical regions designed to be more stable over time and consistent in size than existing administrative and political boundaries. LSOAs comprise, on average, 600 households that are combined on the basis of spatial proximity and homogeneity of dwelling type and tenure. Neighbourhoods are often operationalised as LSOAs.

So to get some boundary data, you can use the UK Data Service website. There is a simple Boundary Data Selector(link text: https://borders.ukdataservice.ac.uk/bds.html)

When you get to the link, you will see on the top there is some notification to help you with the boundary data selector. If you are feeling unsure at any point, feel free to click on that help to guide you.

For now, let’s focus on the selector options. Here you can choose the country you want to select shapefiles for. We select “England”. You can also choose the type of geography we want to use. Here we select “Statistical Building Block”, as discussed above. And finally you can select when you want it for. If you are working with historical data, it makes sense to find boundaries that match the timescale for your data. Here we will be dealing with contemporary data, and therefore we want to be able to use the newest available boundary data. ***

Once you have selected these options, click on the “Find” button. That will populate the box below:

Here you can select the boundaries we want. As discussed, we want the census lower super output areas. But again, your choice here will depend on what data you want to be mapping.

Once you’ve made your choice, click on “List Areas”. This will now populate the box below. We are here concerned with Manchester. However you can select more than one if you want boundarie for more than one area as well. Just hold down “ctrl” to select multiple areas individually, or the shift key to select everything in between.

Once you’ve made your decision click on the “Extract Boundary Data” button. You will see the following message:

You can bookmark, or just stay on the page and wait. How long you have to wait will depend on how much data you have requested to download.

When your data is read, you will see the following message:

You have to right click on the “BoundaryData.zip”, and hit Save Target as on a PC or Save Link As on a Mac:

Navigate to the folder you have created for this analysis, and save the .zip file there. Extract the file contents using whatever you like to use to unzip compressed files. You should end up with a folder called “BoundaryData”. Have a look at its contents:

So you can see immediately that there are some documentations around the usage of this shapefile, in the readme and the terms and conditions. Have a look at these as they will contain information about how you can use this map. For example, all your maps will have to mention where you got all the data from. So since you got this boundary data from the UKDS, you will have to note the following:

“Contains National Statistics data © Crown copyright and database right [year] Contains OS data © Crown copyright [and database right] (year)”

You can read more about this in the terms and conditions document.

But then you will also notice that there are 4 files with the same name “england_oac_2011”. It is important that you keep all these files in the same location as each other! They all contain different bits of information about your shapefile:

  • .shp — shape format; the feature geometry itself - this is what you see on the map
  • .shx — shape index format; a positional index of the feature geometry to allow seeking forwards and backwards quickly
  • .dbf — attribute format; columnar attributes for each shape, in dBase IV format.
  • .prj — projection format; the coordinate system and projection information, a plain text file describing the projection using well-known text format

Sometimes there might be more files associated with your shapefile as well, but we will not cover them here.

Getting spatial data into QGIS

There are two ways to open up a vector shapefile in QGIS. One is to use the “Add Vector Layer” button on the top left hand side:

This will open up a dialogue box:

Where you can click on the “Browse” button and navigate to your shapefile, and select it. Make sure you are choosing the one with the .shp file extension.

Select the file, click on open, and then you will be taken back to the dialogue box where you click “Open”:

Now you will be able to see your shapefile! Yay!

The other way is to very simply drag and drop the shapefile into the QGIS map window. Again, make sure that you are doing this with the file that has the .shp extension!

Find out about your shapefile

Once you have your shapefile in the QGIS environment, you can find out some information about it. You can double click its name in your layers pane, to open up a new window with this information.

If you click on the General tab, it tells you some information about your layer, for example it tells you the CRS. You can see here that the CRS is British National Grid. If it weren’t we could change it in this window as well, using the drop down menu here.

You can also have a look at other tabs, but we won’t get to that just now. Instead we will have a look at the attribute table (if you just wanted to look at the columns in the attribute data you could click the “field” tab here)

So close the window, and this time right click the layer name, and choose “open attribute table”

This will open up a table that should look familiar. As discussed, your rows are your observations, and your columns your variables.

Not too many variables in there at the moment.

You can also get information from the shapefile. By clicking on the little information arrow, and then with that selecting a LSOA, you get the information from that LSOA:

Right now let’s consider that we want to add some data to this map.

Getting non spatial data into QGIS

So it’s quite easy and intuitive to get spatial data in here. But non spatial data can only be mapped if it is linked with spatial information. The main way that this will happen, is that your non-spatial data will have some sort of spatial information still included with it. I will demonstrate here with some police recorded crime data, which can be downloaded from the police.uk website.

Let’s stick local and download some data for crime in Manchester.

To do this, open the data.police.uk/data website.

  • In Date range just select June 2016 - June 2016
  • In Force find Greater Manchester Police, and tick the box next to it.
  • In Data sets tick Include crime data.
  • Finally click on Generate File button.

This will take you to a download page, where you have to click the Download now button. This will open a dialogue to save a .zip file. Navigate to the working directory folder you’ve readet and save it there. Unzip the file.

If you want you can have a look at this data in Excel or something. You will see that there are actually coordinated associated with this data. Let’s ignore that for a second, and pretend that there are none. So then we would look for other types of information. Another column you might notice is the one called LSOA code. If you recall our variables in the LSOA boundary data file, one of these was code. So how will we map this data that is not spatial? You guessed it, by joining them up on a matching column!

So to do this, let’s get our non-spatial crime data into the QGIS environment. To do this we use the Add Delimited Text Layer button which will make a new window popup:

Click on “Browse” button next to the “File Name” bar, and navigate to your .csv file. Select it, and then when you get back to this dialogue box, select “CSV” for “File format”, and then on the “Geometry Definition” option, select “No geometry (attribute only table)”. Like so:

Then click on “OK” and you will see your new attribute table appear in your layers window:

You can right click this, and select “Open Attribute Table” to see all the data that is there.

Now this is not spatial data. Unlike the shapefile, it does not appear on the map. It is only a table of data. For it to appear on the map, it needs to be joined to a spatial layer. We can do this because it has a matching column to an existing spatial layer that we have.

Read in spatial points

Now you must have noticed that our police data actually does have a latitude and longitude column. Because of this, we can actually read it in as spatial data. Let’s give this a go.

To do so, again click on the Add Delimited Text Layer button. Again navigate to the downloaded police data, but this time, click the “Point coordinates” option under “Geometry definition”. You can then select your X and Y coordinates. X should be the column for longitude, and Y the column for latitude.

When you’ve specified all this, click OK and watch your points get added to the map!

You can see that the points cover a lot more area than what our polygon shapefile for Mancheser covers. This is because Greater Manchester Police cover… well Greater Manchester, which also includes for example Bolton and Bury as well. But let’s say here we’re only interested in those in the Borough of Manchester. In this case, our shapefile is just fine. If you were interested in all, you can go back, and when downloading the boundary data select all the boundaries that would be relevant.

You can also have a look at information about this layer, as you did with the boundary layers. If we look at the projection here, we see that it is actually not British National Grid, but is WGS84.

This is the coordinate system that anything with latitude/longitude coorinated will follow. If these were British National Grid points, we would expect the coordinated to be Eastings and Northings.

So what does this mean. Well actually our two spatial layers are on two different coordinate systems. This can cause problems when we try to carry out spatial manipulations, such as count the number of points in each neighbourhood. So before we move on to that, we need to do some reprojections.

Reporojection

So reprojection is very easy in QGIS. All you have to do, is double click on the layer you want to change, and select CRS, and select a new one from the dropdown menu. Sometimes however this has strange results, and also if you want to use this layer as such again, it might be worth saving a new spatial layer with your new projection.

To do this, right click on your layer name, and select “Save As…” This will open up a dialogue box. Select where to save, and give your new layer a name. Then on CRS, click on the dropdown menu, and select the project CRS, which is British National Grid:

Make sure you have selected “Add saved file to map” and then click OK. You will see your new layer appear, now in the same CRS as your boundary data. We can now count the numbers of these points (crimes) in each LSOA (neighbourhood).

Counting the number of points in a polygon

OK so how many crimes are there in each neighbourhood? Well there is an easy way to answer this question, using the points in polygon function. You can find this under Vector > Analysis Tools > Points in Polygon…

Click this to open up a dialogue window.

Here you have to select the points you want to count, the polygon you want to count them in, and the name you want your count column to have. You then select where to save this new shapefile that will have the new column, and once you have that, click on “OK”. Make sure that “add to canvas” is also checked.

Your new layer will have appeared in your window.

Now let’s clean this up a bit. If you click the blue box next to the layer name, you make that layer invisible. Untuck all the boxes except for our new crimes_in_manchester layer. We can now create a thematic map from this new crimes column, to have a look at which neighbourhoods (LSOAs) had higher volume of crimes in June 2016. Exciting!

Create a thematic map

Now we want to visualise which neighbourhoods have more crimes and which have less. To do this, again double click the new crimes_in_manchester layer, and navigate to the Style tab.

On the top dropdown menu, where it says “Single Symbol”, select “Graduated”. This means that you are choosing a continuous variable (numeric) to shade the neighbourhoods by. If you had a qualitative variable (categorical) then you would select the “Categorized” option.

Then, under “Column” select the variable you want to shade by. Here we select the “crimes” column.

Now at this point I want to draw your attention to the “Classes” and “Mode” options. These determine what your map will look like. Classes determined the number of groups you will have. Here we split the neighbourhoods into 5 groups. But if you are looking to rate something on a red amber green scale for example for police, you would want this to only have 3 categories. Similarly the Mode you choose will depend on what you want to say with your data. There is no right or wrong option, but it depends very much on the question you’re asking.

So let’s try using the 5 classes with the equal interval mode. To do this, select these options, and click on the “Classify” button on the left just under that (currently) blank window. You will now see the classes appear. Once they appeared, click “OK”. Let’s see

What story does this map tell? You can see that we have equal interval, the groups are broken up by 100 crimes. You can see that most neighbourhoods in Manchester have between 1-100 crimes. There are a few (you can see actually that they are the larger ones) that have between 100-199. And then you have city centre, where you have the majority of the crimes recorded.

Let’s look at using equal count (quantiles) as your Mode. This splits your neighbourhoods into 5 equal groups. If you used three groups, this would be your low-medium-hihg groups. This way it’s more like lowest-lower-medium-higher-highest groups.

Now city centre still lights up, as do the neighbourhoods that seem to cover larger areas. So we should note something here about counts versus rates, even though this tutorial is not about crimes but about mapping. Always keep in mind what you’re mapping! Here you are mapping number or crimes, and not rate. So we are not controlling for population. You could do this by also attaching some census population data to the shapefile, and creating a new column by dividing the crime column with a population column.

You can get the population data by LSOA from here: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/lowersuperoutputareapopulationdensity

Download and unzip the data, and you will see that actually it is in excel format. To save it as a .csv you can open it up with excel, select the secont tab (called “Mid-2015 Density”). Then click on File > Save as… and navigate to your folder, give it a name, and for file type select comma separated value (.csv).

Then go back to QGIS, and using the Add Delimited Text Layer button, import this new csv. Remember that it has no geometry, and that you want it as an attribute table only.

Then, when it’s in QGIS, join the table, using the LSOA code column to your crimes_in_manchester layer. If you are unsure, scroll up to earlier in this tutorial and follow these steps.

Now if everything went well, then you should have some new columns in your attribute table for the crimes_in_manchester layer. Right click it and view the attribute table to see:

So we see the crimes column, and the mid 2015 population. Population is measured every census. Our most recent one was 2011. However, you do get estimates of population in between censuses. That is what we have here.

Now the final step is to create a new column, by manipulating our existing columns. To do this, you can use the Field calculator. Open this by clicking the little abacus icon on the top right:

This will open the field calculator window.

In the top, above the calculation window is where we tell field calculator to create a new variable, we give this variable a name, and we select if this should be a string (characters), and integer (whole numbers), a real number (with decimals), or a date.

Now we have a few issues. Firstly, the population variable, is unhelpfully not a numer. It has a comma, and so it looks like a character variable. So first we create a new population variable, which is numeric:

***

So to do this we need to be removing the “,”. We can do this using the replace() function. Inside the function, we need to say what field we are replacing the text in, what we are replacing, and what with. So if we want to replace “,” with “” (nothing) in the “population_Mid-2015 population” field we need to type

 replace("population_Mid-2015 population", ',', '')

like so: ***

Then, when done, click “OK”

So now you have a new variable. And we can use this to calculate a crime rate. Open up the Field Calculator again, and this time, the equation we enter is a simple division, plus a multiplication (we normally talk about crime rate per 100,000 population, not per person, so let’s multiply by 100,000)

You can learn more about the field calculator expressions here and here

Now, you can go back to the Style tab, and use this new crime_rate variable to create your thematic map.

It should look something like this:

Does that look different? Well this is up to you, the researcher to discuss!

Saving your map

Anyway that is all I have for you now. You will of course also have to save your map. For this you can use the print composer. You open that by clicking this icon:

Here is an excellent video you can watch that will walk you through how to export your map using this print composer.

Parting words

As I said at the beginning there is loads of help online for QGIS. If you want to know how to do something, just google it. For example, if you want to know how to make a heatmap in QGIS, just google “HOW TO MAKE A HEATMAP IN QGIS” and I guarantee that you will find a nice step-by-step tutorial to follow online.

If you are stuck though, and need some help, don’t hesitate to get in touch and email me at reka.solymosi@manchester.ac.uk